AWS DeepLens is a $249 Deep Learning Video Camera for Developers

The camera can not only do inference, but also train deep learning models using Amazon infrastructure. Performance wise, the camera can infer 14 images/second on AlexNet, and 5 images/second on ResNet 50 for batch size of 1.

Six projects samples are currently available: object detection, hot dog not hot dog, cat and dog,  activity detection, and face detection. Read that blog post to see how to get started.

But if you want to make your own project, a typical workflow would be as follows:

• Train a deep learning model using Amazon SageMaker
• Optimize the trained model to run on the AWS DeepLens edge device
• Develop an AWS Lambda function to load the model and use to run inference on the video stream
• Deploy the AWS Lambda function to the AWS DeepLens device using AWS Greengrass
• Wire the edge AWS Lambda function to the cloud to send commands and receive inference output

This steps are explained in details on Amazon blog.

Intel also published a press release explaining how they are involved in the project:

DeepLens uses Intel-optimized deep learning software tools and libraries (including the Intel Compute Library for Deep Neural Networks, Intel clDNN) to run real-time computer vision models directly on the device for reduced cost and real-time responsiveness.
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